Seasonal patterns of water quality and phytoplankton dynamics in surface waters in Guangzhou and Foshan, China

During 2015, we studied the temporal patterns of nutrient concentrations and turbidity in water bodies with different degrees of agricultural and urban pressures across Guangzhou and Foshan (China). Data and observations were made by trained citizen scientists and professional researchers. Our study shows that all monitored water bodies, with the exception of Qiandeng Lake and Fengjiang River, had elevated NO(3) over bar -N concentrations, which ranged from 0.10 to 6.83 mg/L and peaked in late winter and early spring and reached a minimum in summer and mid-autumn. Po43-P concentrations ranged from 0.01 to 025 mg/L and peaked during the winter, late-summer and late autumn. Turbidity values were highest at sites with agricultural activities, with maximums in the late winter and autumn, and the highest frequency (16% and 25%) of algae presence occurred in the spring and autumn. To better understand the characteristics and drivers of the algae occurrences, measurements of phytoplankton composition and physicochemical characteristics were conducted in three key seasons in the agricultural process, fallow, sowing and rainy season in 2016. Our focused study found that the occurrence of Bacillariophyta, Euglenophyta, Xanthophyta, Cryptophyta, Chrysophyta were positively correlated with dissolved oxygen and phosphorus concentrations, while Chlorophyta and Cyanophyta had positive correlations with turbidity, oxygen demand and nitrogen concentrations. Bacillariophyceae counted for the highest proportion of phytoplankton during the fallow season, comprising up to 60 +% of the phytoplankton among the sites. During the rainy season, Chlorophyceae species were the majority, comprising up to 90 +% of phytoplankton among the sampled sites. Our results pointed to the complexity of nutrient and phytoplankton dynamics in water bodies under multiple pressures, and to the value of using citizen scientists to determine contextual information to benefit more focused studies. (C) 2017 Elsevier B.V. All rights reserved.